Malaria is very highly endemic in the Democratic Republic of the Congo (DRC). We propose to use >16,000 dried blood spots from the 2007 and 2012 Demographic and Health Surveys (DHS) in the DRC to conduct the first longitudinal, nation-wide study of malaria genetic epidemiology. We have already measured and mapped malaria in the DRC from the 2007 DHS by high-throughput real-time PCR. Our first aim is to determine the effects of malaria control efforts on the prevalence of P. falciparum and other malaria species. We have a unique opportunity to do this now; malaria control programs were minimal in 2007 but are being dramatically scaled up this year (by the Global Fund, USAID and other agencies). Multilevel modeling will be used to identify individual- and cluster-level variables associated with increases or decreases in malaria prevalence. Our second aim is to measure molecular markers of drug resistance (dhps, pfcrt and pfmdr1) in P. falciparum samples from 2007 and 2012, and identify individual- and cluster-level factors associated with changes in the prevalence of drug resistance. Our third aim is to measure neutral microsatellite markers in P.falciparum from 2007 and 2012. Landscape genetic analyses will measure genetic distances in the P. falciparum populations between clusters and over time. This will allow the identification of dispersal corridors and barriers. It will also permit estimation of the rate of gene flow. The latter could be used to predict the rate at which malaria might reinvade an area from which it was eliminated. Taken together, our findings could offer a scientific foundation for malaria control programs.